Название: Mathematics for Digital Science, Volume 2: Digital Information
Автор: Gérard-Michel Cochard, Mhand Hifi
Издательство: Wiley-ISTE
Год: 2025
Страниц: 353
Язык: английский
Формат: pdf (true)
Размер: 15.1 MB

Over the past century, advancements in Computer Science have consistently resulted from extensive mathematical work. Even today, innovations in the digital domain continue to be grounded in a strong mathematical foundation. To succeed in this profession, both today’s students and tomorrow’s computer engineers need a solid mathematical background. The goal of this book series is to offer a solid foundation of the knowledge essential to working in the digital sector. The three-volume work compiles the lessons taught to numerous generations of students in the first two university cycles, specifically in bachelor’s/master’s degrees in Computer Science or in Computer Methods Applied to Business Management. The second – and present – volume focuses on digital information, while the third volume is devoted to data analysis and optimization. Chapters 1 and 2 of this second volume address the representation of information (such as numbers, texts, images, sounds, videos, labels) in the form of combinations of 0s and 1s. This binary representation facilitates the processing, analysis and transmission of information using computer resources. Chapter 3 addresses the classification of communication signals, both analog and digital, and introduces Fourier series analysis for periodic signals. Chapter 4 presents mathematical tools for signal analysis, including z-transforms, Fourier transforms and Laplace transforms.

Название: Mathematics for Digital Science 3: Data Analysis and Optimization
Автор: Gérard-Michel Cochard, Mhand Hifi
Издательство: Wiley-ISTE
Год: 2025
Страниц: 322
Язык: английский
Формат: pdf
Размер: 19.9 MB

Over the past century, advancements in computer science have consistently resulted from extensive mathematical work. Even today, innovations in the digital domain continue to be grounded in a strong mathematical foundation. To succeed in this profession, both today's students and tomorrow’s computer engineers need a solid mathematical background. The goal of this book series is to offer a solid foundation of the knowledge essential to working in the digital sector. Across three volumes, it explores fundamental principles, digital information, data analysis, and optimization. Whether the reader is pursuing initial training or looking to deepen their expertise, the Mathematics for Digital Science series revisits familiar concepts, helping them refresh and expand their knowledge while also introducing equally essential, newer topics.

Название: Fostering Machine Learning and IoT for Blockchain Technology: Smart Cities Applications, Volume 2
Автор: Khaleel Ahmad, Uma N. Dulhare, Mohammad Sufian Badar, Jameel Ahamed, M.A. Rizvi
Издательство: Springer
Серия: Transactions on Computer Systems and Networks
Год: 2025
Страниц: 311
Язык: английский
Формат: pdf (true), epub
Размер: 52.1 MB

The book covers Blockchain Technology and its emerging field by developing socio-economic systems viz. efficiently establishing transparency, trust, increasing utilization of various resources, and reducing costs. This book is organized into 2 volumes that provide an overview of Blockchain technology foundations of Blockchain, Machine Learning and Distributed Systems, Cryptography, Consensus algorithm, Bitcoin concepts, and its properties, Smart Contracts, developing knowledge of tools like Hyperledger, Multichain, Ethereum, etc. Machine Learning algorithms, applications of a smart city using Machine Learning and blockchain technology. While this book dwells on the foundations of Blockchain Technology as a part of transparency, scalability, integrity, security, and how the Machine Learning algorithms integrate with blockchain technology-based smart city applications, it will also focus on contemporary topics for Research and Development in various sectors. With an in-depth knowledge of the technology underlying various platforms such as Bitcoin, Ethereum, and Hyperledger.

Название: Ultimate Agentic AI with AutoGen for Enterprise Automation: Design, Build, And Deploy Enterprise-Grade AI Agents Using LLMs and AutoGen To Power Intelligent, Scalable Enterprise Automation
Автор: Shekhar Agrawal, Srinivasa Sunil Chippada, Rathish Mohan
Издательство: Orange Education Pvt Ltd, AVA
Год: 2025
Страниц: 365
Язык: английский
Формат: epub (true)
Размер: 53.0 MB

Empowering Enterprises with Scalable, Intelligent AI Agents. In an era where Artificial Intelligence (AI) is transforming enterprises, Large Language Models (LLMs) are unlocking new frontiers in automation, augmentation, and intelligent decision-making. Ultimate Agentic AI with AutoGen for Enterprise Automation bridges the gap between foundational AI concepts and hands-on implementation, empowering professionals to build scalable and intelligent enterprise agents. The book begins with the core principles of LLM agents and gradually moves into advanced topics such as agent architecture, tool integration, memory systems, and context awareness. Readers will learn how to design task-specific agents, apply ethical and security guardrails, and operationalize them using the powerful AutoGen framework. This book is tailored for AI/ML engineers, software developers, data scientists, solution architects, enterprise tech leads, product managers, innovation strategists, and CTOs.

Название: Probing the Past with Data Analytics and AI
Автор: Marc Thuillard
Издательство: World Scientific Publishing
Год: 2025
Страниц: 260
Язык: английский
Формат: pdf (true)
Размер: 11.4 MB

This comprehensive compendium explains the technical challenges and opportunities behind the most recent and successful applications in Artificial Intelligence [AI] and data analytics. It focuses on applications that have the power to be adapted to many different fields and explains how AI can be implemented as an assistant in digital humanities. It also introduces new methods and applications in classification trees, networks, and Bayesian learning. The useful reference text benefits professionals, academics, researchers, and graduate students in AI/Machine Learning, neural networks, and bioinformatics, and digital humanities. The first chapter briefly introduces the most important classical classification techniques. The choice was set on methods that find broad applications in data analytics and AI further in the book. In this chapter, as in the rest of this book, we follow the strategy to explain and illustrate the main ideas behind the most advanced AI with minimal use of equations. The reader is furnished with many good references to enquire further. The second chapter is on a family of Neural Networks described by the acronym “CNN”, which stands for convolutional neural networks.

Название: Любимая/Лучшая книги рисования, раскрасок, ребусов, головоломок и оригами
Автор: Фёдорова Екатерина
Изд-во: Х.: Аргумент Принт
Год: 2013
К-во стр. : 2*40
Формат: pdf
Размер: 15,85 Мб
Язык: русский

Головоломки и лабиринты, задания и ребусы, уроки рисования с пошаговыми иллюстрациями и комментариями, простые и понятные схемы изготовления поделок из листа бумаги.
● Любимая книга рисования, раскрасок, ребусов, головоломок и оригами.
● Лучшая книга рисования, раскрасок, ребусов, головоломок и оригами.

Название: Радиолокационные методы селекции движущихся целей
Автор: Бакулев П.А.
Издательство: Оборонгиз
Год издания: 1958
Количество страниц: 103
Язык: русский
Формат: DjVu, PDF
Размер: 22,06 Мб

В учебном пособии излагаются основные радиолокационные методы селекции движущихся целей (СДЦ) и их применение в системах селекции движущихся целей. Дается характеристика сигналов движущихся и неподвижных целей и мешающих сигналов. Рассматриваются способы компенсации сигналов неподвижных объектов. Дается анализ особенностей работы различных систем СДЦ и рассматриваются различные факторы, влияющие на качество работы устройств селекции, а также способы повышения качества селекции в радиолокаторах СДЦ.

Название: Visual Object Tracking: An Evaluation Perspective
Автор: Xin Zhao, Shiyu Hu, Xu-Cheng Yin
Издательство: Springer
Серия: Advances in Computer Vision and Pattern Recognition
Год: 2025
Страниц: 202
Язык: английский
Формат: pdf (true)
Размер: 21.1 MB

This book delves into visual object tracking (VOT), a fundamental aspect of computer vision crucial for replicating human dynamic vision, with applications ranging from self-driving vehicles to surveillance systems. Despite significant strides propelled by Deep Learning, challenges such as target deformation and motion persist, exposing a disparity between cutting-edge VOT systems and human performance. This observation underscores the necessity to thoroughly scrutinize and enhance evaluation methodologies within VOT research. Hence, the primary objective of this book is to equip readers with essential insights into dynamic visual tasks encapsulated by VOT. Beginning with the elucidation of task definitions, it integrates interdisciplinary perspectives on evaluation techniques. Pursuing dynamic visual intelligence represents one of the most significant challenges in Artificial Intelligence (AI), requiring the synthesis of perceptual acuity, cognitive reasoning, and real-time adaptability. This book addresses these challenges, positioning itself at the intersection of cognitive science, Computer Vision, and Machine Learning.

Название: MICKEY ET SES AMIS - Les Ateliers - Coloriages mystères - Disney
Иллюстратор: Vincent Jaunatre, Emeline Jaunatre
Изд-во: DISNEY HACHETTE
Год: 2018
Жанр: раскраска / Coloring book
К-во стр.40
Формат: PDF
Размер: 71,59 Мб
Язык: French

This color by number book is a must have for anyone who loves Disney. Simplified color palette
Grâce au code couleurs, les enfants vont découvrir de merveilleux dessins cachés sur chacune des pages de ce livre. Une belle façon de redécouvrir Mickey et tous ses amis à l'occasion des 90 ans de la souris la plus connue au monde !

Название: Derivative-Free Optimization: Theoretical Foundations, Algorithms, and Applications
Автор: Yang Yu, Hong Qian, Yi-Qi Hu
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2025
Страниц: 194
Язык: английский
Формат: pdf (true), epub
Размер: 34.1 MB

This book offers a pioneering exploration of classification-based derivative-free optimization (DFO), providing researchers and professionals in Artificial Intelligence (AI), Machine Learning (ML), AutoML, and optimization with a robust framework for addressing complex, large-scale problems where gradients are unavailable. By bridging theoretical foundations with practical implementations, it fills critical gaps in the field, making it an indispensable resource for both academic and industrial audiences. The book introduces innovative frameworks such as sampling-and-classification (SAC) and sampling-and-learning (SAL), which underpin cutting-edge algorithms like Racos and SRacos. These methods are designed to excel in challenging optimization scenarios, including high-dimensional search spaces, noisy environments, and parallel computing. A dedicated section on the ZOOpt toolbox provides practical tools for implementing these algorithms effectively. The book’s structure moves from foundational principles and algorithmic development to advanced topics and real-world applications, such as hyperparameter tuning, neural architecture search, and algorithm selection in AutoML. A foundational understanding of Machine Learning, probability theory, and algorithms is recommended for readers to fully engage with the material.